EMA Crossover Strategy with S/R and Cross Exits v6Was macht diese Strategie?
Diese Strategie kombiniert bewährte technische Indikatoren mit einem robusten Risikomanagement, um klare Kauf- und Verkaufssignale in trendstarken Märkten zu generieren. Sie basiert auf dem Crossover von exponentiellen gleitenden Durchschnitten (EMA) in Kombination mit einem Trendfilter aus dem höheren Zeitrahmen und einem dynamischen Risikomanagement basierend auf der durchschnittlichen True Range (ATR).
Wie funktioniert die Strategie?
Kernsignale:
Kauf: Wenn der EMA5 (kurzfristig) von unten die EMA8 und EMA13 kreuzt.
Verkauf: Wenn der EMA5 von oben die EMA8 und EMA13 kreuzt.
Trendfilter:
Es wird nur gehandelt, wenn der Preis über dem 200-EMA aus dem 1-Stunden-Chart liegt (für Longs) oder darunter (für Shorts). Dies stellt sicher, dass Sie nur in Richtung des übergeordneten Trends handeln.
Risikomanagement:
Dynamischer Stop-Loss: Basierend auf der ATR (durchschnittliche True Range), um die Volatilität des Marktes zu berücksichtigen.
Take-Profit: Ein festgelegtes Risiko-Ertrags-Verhältnis von 1:2, um Gewinne zu sichern und Verluste zu begrenzen.
Positionsgröße: Die Positionsgröße wird basierend auf dem Kontostand und dem Risiko pro Trade angepasst, um das Risiko zu kontrollieren.
Zusätzliche Filter:
RSI-Filter: Es wird nur gekauft, wenn der RSI überverkauft ist (<30), und nur verkauft, wenn der RSI überkauft ist (>70).
Volumenfilter: Es wird nur gehandelt, wenn das aktuelle Volumen über dem Durchschnitt liegt, um sicherzustellen, dass genügend Liquidität vorhanden ist.
Warum diese Strategie?
Einfachheit: Klare Regeln und leicht verständliche Signale.
Anpassungsfähigkeit: Die Strategie passt sich der Marktvolatilität an (dank ATR-basiertem Stop-Loss).
Trendfolge: Durch den Trendfilter aus dem höheren Zeitrahmen werden nur Trades in Richtung des übergeordneten Trends ausgeführt.
Risikokontrolle: Dynamisches Risikomanagement sorgt dafür, dass Verluste begrenzt und Gewinne maximiert werden.
Erfolgschancen
Profitfaktor: Die Strategie zielt auf einen Profitfaktor von mindestens 1,5 ab, was bedeutet, dass die Gewinne die Verluste deutlich übersteigen.
Gewinnwahrscheinlichkeit: Durch die Kombination von Trendfiltern und RSI-Signalen wird die Wahrscheinlichkeit erfolgreicher Trades erhöht.
Backtest-Ergebnisse: In historischen Tests zeigt die Strategie konsistente Ergebnisse in trendstarken Märkten.
Risiken
Seitwärtsmärkte: In trendlosen oder choppigen Märkten kann die Strategie zu häufigen Fehlsignalen führen.
Volatilitätsspitzen: Extreme Marktbewegungen können zu unerwarteten Stop-Loss-Auslösungen führen.
Overfitting: Die Strategie wurde zwar optimiert, aber historische Performance ist keine Garantie für zukünftige Ergebnisse.
Emotionen: Disziplin ist erforderlich, um die Regeln strikt zu befolgen.
Für wen ist diese Strategie geeignet?
Einsteiger: Dank klarer Regeln und einfacher Signale ist die Strategie auch für weniger erfahrene Trader geeignet.
Erfahrene Trader: Die Anpassungsfähigkeit und das Risikomanagement bieten auch fortgeschrittenen Tradern eine solide Grundlage.
Langfristige Anleger: Die Strategie eignet sich für Trader, die auf mittel- bis langfristige Trends setzen möchten.
Warum jetzt buchen?
Sofortige Umsetzbarkeit: Die Strategie ist sofort einsatzbereit und kann in jedem Marktumfeld angewendet werden.
Persönliche Anpassung: Wir passen die Strategie an Ihre individuellen Risikopräferenzen und Handelsziele an.
Unterstützung: Sie erhalten eine detaillierte Anleitung und kontinuierlichen Support, um die Strategie erfolgreich umzusetzen.
Fazit
Diese Strategie bietet eine ausgewogene Mischung aus Einfachheit, Anpassungsfähigkeit und Risikokontrolle. Sie ist ideal für Trader, die eine systematische und regelbasierte Herangehensweise suchen, um in trendstarken Märkten konsistente Gewinne zu erzielen.
Buchen Sie jetzt und starten Sie Ihre Trading-Reise mit einer bewährten und optimierten Strategie! 🚀
Bands and Channels
ForexMasterStochastic//@version=5
indicator(title="ForexMasterStochastic", shorttitle="Stoch", format=format.price, precision=2, timeframe="", timeframe_gaps=true)
periodK = input.int(14, title="%K Length", minval=1)
smoothK = input.int(3, title="%K Smoothing", minval=1)
periodD = input.int(3, title="%D Smoothing", minval=1)
k = ta.sma(ta.stoch(close, high, low, periodK), smoothK)
d = ta.sma(k, periodD)
plot(k, title="%K", color=#2962FF)
plot(d, title="%D", color=#FF6D00)
h0 = hline(80, "Upper Band", color=#787B86)
hline(50, "Middle Band", color=color.new(#787B86, 50))
h1 = hline(20, "Lower Band", color=#787B86)
fill(h0, h1, color=color.rgb(33, 150, 243, 90), title="Background")
Bollinger Bands StrategyBeginner strategy to know easy buy and sell strategy with no decent knowledge of levels
Combined Stochastic, ADX & BreakoutTrading View Indicator Explanation
Entry Signal Logic
This indicator identifies two specific buying opportunities during an uptrend following a correction:
Entry Signal #1 - Post-Correction Breakout
Wait for price to establish an uptrend above EMA9
Look for at least one lower high (correction)
Entry trigger: Breakout above the previous candle's high
Stop loss: Place below the most recent swing low
Entry Signal #2 - Strong Trend Correction
Requires a blue triangle marker above the candle (on closing basis)
Must occur during a strong uptrend (confirmed by high ADX reading)
Requires a deep technical correction (measured by Stochastic)
Entry conditions:
Price must be above EMA9
Current candle must break above previous candle's high
Stop loss: Place below the most recent swing low
Notes
Sell signals have been removed to reduce chart clutter
Recommended exit strategy: Sell at new swing highs
The second signal specifically filters for stronger trend conditions
Technical Indicators Used
EMA9: Trend direction filter
Stochastic: Measures depth of correction
ADX: Confirms strength of uptrend
Price action: Candle high/low relationships
This is designed to catch continuation moves in established uptrends after healthy corrections, emphasizing high-probability entries with clearly defined stop levels.
200-SMA, 20-EMA & VWAPThis custom TradingView indicator combines three powerful tools to help traders identify trends and key price levels:
✅ 200-SMA (Simple Moving Average) – A long-term trend indicator used to gauge overall market direction.
✅ 20-EMA (Exponential Moving Average) – A short-term moving average that reacts faster to price changes, helping with entry and exit points.
✅ VWAP (Volume Weighted Average Price) – A key institutional trading level that represents the average price weighted by volume, often used for determining fair value.
🔹 Features:
• Toggle on/off for each indicator
• Customizable colors
• Clean and minimalistic display
Ideal for day traders, swing traders, and investors looking to refine their market analysis.
FII Option Chain Activitytrying to detect FII activity
based on
rank volatility
straddle
strangle
etc
etc
Turtle Trading Mejorado para BTC 1Hturtle trading adapated to 1h
Canales Donchian:
Entrada: Periodo de 20 para detectar rupturas (largas y cortas).
Salida: Periodo de 10 para cerrar posiciones.
ATR (Average True Range):
Periodo de 14 para medir volatilidad y calcular el tamaño de las posiciones.
Gestión de Riesgo:
Riesgo por operación: 2% del capital.
Máximo de 4 unidades por posición.
Condiciones de Entrada:
Larga: Precio alto supera el máximo de 20 periodos.
Corta: Precio bajo cae por debajo del mínimo de 20 periodos.
Condiciones de Salida:
Larga: Precio bajo cae por debajo del mínimo de 10 periodos.
Corta: Precio alto supera el máximo de 10 periodos.
Añadir Unidades:
Se añaden unidades si el precio se mueve 0.5 ATR a favor, hasta 4 unidades.
Stop Loss:
Dinámico, basado en 2 ATR desde el precio de entrada.
FVG, Supply/Demand, Order Blocks with Volume & RSI Divergenceits a beginners analysis of using different strategies
SMA and EMA CloudEMA and SMA line cloud that shows when the 2 moving averages are either close or wide range, indicating volume and volatility.
Triple Moving Average with LabelsThis indicator "Triple Moving Average with Labels", overlays the 50, 100, and 200 period Simple Moving Averages (SMAs) on the chart and provides customizable floating labels for each line. By default, the labels display "50 MA", "100 MA", and "200 MA", but users can modify or remove the text entirely through the indicator settings. The moving average periods (50, 100, or 200) are also adjustable. The labels are positioned slightly above and to the right of their respective lines for clear visibility.
Custom MA Indicator// @version=6
indicator("Custom MA Indicator", overlay=true)
// Define the moving average periods
ma_red_period = 50
ma_orange_period = 100
ma_green_period = 200
// Calculate the moving averages
ma_red = ta.sma(close, ma_red_period)
ma_orange = ta.sma(close, ma_orange_period)
ma_green = ta.sma(close, ma_green_period)
// Plot the moving averages with specified colors
plot(ma_red, color=color.red, title="Red MA")
plot(ma_orange, color=color.orange, title="Orange MA")
plot(ma_green, color=color.green, title="Green MA")
EMA + RSI Bullish Reversal with Target and Stop LossEMA + RSI Bullish Reversal with Target and Stop Loss
EMA Condition: 9 EMA is above the 21 EMA (indicating an uptrend).
RSI Condition: RSI is below 30 (indicating an oversold condition).
Entry Condition: When RSI crosses above 30, confirming a bullish reversal in an uptrend (9 EMA > 21 EMA), take a long position.
Target: Close the position when the price moves up by 0.5% from the entry.
12/21 ema 4x and 16x48/84/192/336 EMA. Plots the 12/21 ema on 4x and 16x scale.
This indicator displays 12 and 21 period EMAs, scaled to 4x and 16x the current chart's timeframe. This allows you to visualize higher timeframe 12/21 EMAs directly on your current chart, such as showing the 1-hour and 4-hour equivalent 12/21 EMAs on a 15-minute chart.
Machine Learning: Lorentzian Classification/ ====================
// ==== Background ====
// ====================
// When using Machine Learning algorithms like K-Nearest Neighbors, choosing an
// appropriate distance metric is essential. Euclidean Distance is often used as
// the default distance metric, but it may not always be the best choice. This is
// because market data is often significantly impacted by proximity to significant
// world events such as FOMC Meetings and Black Swan events. These major economic
// events can contribute to a warping effect analogous a massive object's
// gravitational warping of Space-Time. In financial markets, this warping effect
// operates on a continuum, which can analogously be referred to as "Price-Time".
// To help to better account for this warping effect, Lorentzian Distance can be
// used as an alternative distance metric to Euclidean Distance. The geometry of
// Lorentzian Space can be difficult to visualize at first, and one of the best
// ways to intuitively understand it is through an example involving 2 feature
// dimensions (z=2). For purposes of this example, let's assume these two features
// are Relative Strength Index (RSI) and the Average Directional Index (ADX). In
// reality, the optimal number of features is in the range of 3-8, but for the sake
// of simplicity, we will use only 2 features in this example.
// Fundamental Assumptions:
// (1) We can calculate RSI and ADX for a given chart.
// (2) For simplicity, values for RSI and ADX are assumed to adhere to a Gaussian
// distribution in the range of 0 to 100.
// (3) The most recent RSI and ADX value can be considered the origin of a coordinate
// system with ADX on the x-axis and RSI on the y-axis.
// Distances in Euclidean Space:
// Measuring the Euclidean Distances of historical values with the most recent point
// at the origin will yield a distribution that resembles Figure 1 (below).
//
// |
// |
// |
// ...:::....
// .:.:::••••••:::•::..
// .:•:.:•••::::••::••....::.
// ....:••••:••••••••::••:...:•.
// ...:.::::::•••:::•••:•••::.:•..
// ::•:.:•:•••••••:.:•::::::...:..
// |--------.:•••..•••••••:••:...:::•:•:..:..----------
// 0 :•:....:•••••::.:::•••::••:.....
// ::....:.:••••••••:•••::••::..:.
// .:...:••:::••••••••::•••....:
// ::....:.....:•::•••:::::..
// ..:..::••..::::..:•:..
// .::..:::.....:
// |
// |
// |
// |
// _|_ 0
//
// Figure 1: Neighborhood in Euclidean Space
// Distances in The Space:
// However, the same set of historical values measured using The Distance will
// yield a different distribution that resembles Figure 2 (below).
//
//
// ::.. | ..:::
// ..... | ......
// .••••::. | :••••••.
// .:•••••:. | :::••••••.
// .•••••:... | .::.••••••.
// .::•••••::.. | :..••••••..
// .:•••••••::.........::••••••:..
// ..::::••••.•••••••.•••••••:.
// ...:•••••••.•••••••••::.
// .:..••.••••••.••••..
// |---------------.:•••••••••••••••••.---------------
// 0 .:•:•••.••••••.•••••••.
// .••••••••••••••••••••••••:.
// .:••••••••••::..::.::••••••••:.
// .::••••••::. | .::•••:::.
// .:••••••.. | :••••••••.
// .:••••:... | ..•••••••:.
// ..:••::.. | :.•••••••.
// .:•.... | ...::.:••.
// ...:.. | :...:••.
// :::. | ..::
// _|_ 0
//
// Figure 2: Neighborhood in the Space
// Observations:
// (1) In the Space, the shortest distance between two points is not
// necessarily a straight line, but rather, a geodesic curve.
// (2) The warping effect of Lorentzian distance reduces the overall influence
// of outliers and noise.
// (3) The Distance becomes increasingly different from Euclidean Distance
// as the number of nearest neighbors used for comparison increases.
Opening Range BoxIndicator Name: Opening Range Box with Extensions
Author: YanivBull
Description:
The Opening Range Box with Extensions is a powerful tool designed to visualize the trading range established during the first 30 minutes of a market session, a critical period for setting the day's trend. This indicator plots a box representing the high and low prices formed within this opening range, with dashed extension lines projecting these levels forward throughout the session.
Its primary purpose is to identify the boundaries of the initial trend at the start of trading. When these boundaries are breached, it serves as a trigger for potential trading opportunities: a breakout above the box high signals a possible long entry, while a breakdown below the box low indicates a potential short entry. The indicator also includes historical boxes for up to 5 previous days (configurable), allowing traders to analyze past opening ranges and their extensions for context and pattern recognition.
Key Features:
Customizable session start time (hour and minute) to adapt to various markets (e.g., NYSE, DAX, etc.).
Displays the current session's opening range box in blue and historical boxes in gray.
Plots dashed extension lines from the high and low of each box, limited to 500 bars or the end of the trading day.
Adjustable number of historical days (1-20, default 5).
Usage:
Set the Session Start Hour and Session Start Minute according to your market's opening time (relative to your chart's timezone, e.g., UTC+2). Watch for price action around the box boundaries—breakouts above the high or below the low can be used as signals for initiating long or short trades, respectively. Combine with other technical analysis tools for confirmation.
This indicator is ideal for day traders looking to capitalize on early session momentum and breakout strategies.
Smart Scalping Momentum StrategyThe Smart Scalping Momentum Strategy is a powerful and well-optimized trading strategy designed for Forex, Crypto, and XAU/USD (Gold) markets. It focuses on high-probability entries based on price momentum, trend confirmation, and volatility adjustments. The strategy aims to maximize daily profits while maintaining a low-risk exposure by utilizing multiple technical indicators and strict risk management rules.
Enhanced Bollinger Bands Strategy for SilverThis strategy uses Bollinger bands, RSI, volumes and trend analysis to provide smooth trades and ride longer trends
SMA High & Low V3📌 Summary of Script Functionality
This script is a custom TradingView indicator designed to analyze market trends using SMA (Simple Moving Averages) and RSI (Relative Strength Index). It consists of the following key components:
1️⃣ SMA High & SMA Low (from H4 timeframe)
- SMA High is calculated from the highest price.
- SMA Low is calculated from the lowest price.
- These are used as support and resistance levels.
2️⃣ SMA Color Coding (Trend Detection)
- Green → When the closing price is above SMA High → Uptrend
- Red → When the closing price is below SMA Low → Downtrend
- Orange → When the price is between SMA High & SMA Low → Ranging market
3️⃣ RSI Marker (Colored Dots Below the Chart)
- RSI (14) is calculated and displayed as colored markers at the bottom.
- Green Dot → RSI > 50 (indicating bullish momentum)
- Red Dot → RSI < 50 (indicating bearish momentum)
📌 Trading Strategy (Entry & Exit Points)
✅ 1. Buy Entry (Long Position)
- Price is above SMA High (SMA turns green)
- RSI > 50 (Green dots appear below the chart)
- Enter a Buy trade when the price pulls back near SMA High and shows a reversal candlestick pattern.
✅ 2. Sell Entry (Short Position)
- Price is below SMA Low (SMA turns red)
- RSI < 50 (Red dots appear below the chart)
- Enter a Sell trade when the price retraces near SMA Low and shows a reversal candlestick pattern.
✅ 3. No Trade Zone (Avoid Trading)
- If SMA is orange (price is between SMA High & SMA Low)
- RSI is unclear → Wait for a breakout before entering a trade.
BXY & DXY Cross (Perfectly Balanced)If you deal with Usd and their pairs and need necssary confirmation You might need this
Bxy and Dxy Index Crossings (GBP Index and Usd Index Crossing)
EXY & DXY Cross (Perfectly Balanced)If you deal with Usd and their pairs and need necssary confirmation You might need this
Exy and Dxy Index Crossings
Oracle Fear and GreedCustom Fear and Greed Oscillator with Movement Table
This indicator provides a unique perspective on market sentiment by calculating a custom fear/greed oscillator based on Heikin-Ashi candles. The oscillator is centered at 50, with values above 50 suggesting bullish sentiment ("greed") and below 50 indicating bearish sentiment ("fear"). The calculation incorporates candle body size, range, and a custom "candle strength" measure, providing an innovative approach to understanding market behavior.
Key Features:
Heikin-Ashi Based Oscillator:
Utilizes Heikin-Ashi candles to compute a custom oscillator. The value is centered at 50, with deviations indicating the prevailing market sentiment.
Dynamic Gradient Coloring:
The oscillator line is dynamically colored with a smooth gradient—from blue (representing fear) at lower values to pink (representing greed) at higher values—making it visually intuitive.
Horizontal Levels:
Two additional horizontal lines are drawn at 40.62 ("Bottom") and 60.74 ("Top"), which may serve as potential oversold and overbought boundaries respectively.
Fast Movement Metrics:
Every 5 bars, the indicator calculates the percentage change in the Heikin-Ashi close. This fast movement analysis distinguishes rapid downward moves (fast fear) from rapid upward moves (fast greed), helping to capture sudden market shifts.
Information Table:
A table in the top-right corner displays the most recent fast movement values for both fear and greed, offering quick insights into short-term market dynamics.
Usage Tips:
Adjust the smoothing period to match your preferred trading timeframe.
Use the oscillator alongside other analysis tools for more robust trading decisions.
Ideal for those looking to experiment with new approaches to sentiment analysis and momentum detection.
Disclaimer:
This indicator is intended for educational and experimental purposes. It should not be used as the sole basis for any trading decisions. Always combine with comprehensive market analysis and risk management strategies.
You can add this description when publishing your indicator on TradingView to help other users understand its features and intended use.
SMA High & LowThis Pine Script indicator plots two Simple Moving Averages (SMA) based on high and low prices over a specified length. It also references the H4 (4-hour) timeframe SMA to determine the color of the lines:
- Green if the current price is above the H4 SMA High.
- Red if the current price is below the H4 SMA Low.
- Orange if the price is between the H4 SMA High and Low.
This helps traders visualize market trends based on higher timeframe SMA levels.
